Air quality modelling in the summer over the eastern Mediterranean using WRF-Chem: chemistry and aerosol mechanism intercomparison

Abstract

Abstract. We employ the WRF-Chem model to study summertime air pollution, the intense photochemical activity and their impact on air quality over the eastern Mediterranean. We utilize three nested domains with horizontal resolutions of 80, 16 and 4 km, with the finest grid focusing on the island of Cyprus, where the CYPHEX campaign took place in July 2014. Anthropogenic emissions are based on the EDGAR HTAP global emission inventory, while dust and biogenic emissions are calculated online. Three simulations utilizing the CBMZ-MOSAIC, MOZART-MOSAIC, and RADM2-MADE/SORGAM gas-phase and aerosol mechanisms are performed. The results are compared with measurements from a dense observational network of 14 ground stations in Cyprus. The model simulates T 2 m , P surf , and WD 10 m accurately, with minor differences in WS 10 m between model and observations at coastal and mountainous stations attributed to limitations in the representation of the complex topography in the model. It is shown that the south-eastern part of Cyprus is mostly affected by emissions from within the island, under the dominant (60 %) westerly flow during summertime. Clean maritime air from the Mediterranean can reduce concentrations of local air pollutants over the region during westerlies. Ozone concentrations are overestimated by all three mechanisms (9 % ≤ NMB ≤ 23 %) with the smaller mean bias (4.25 ppbV) obtained by the RADM2-MADE/SORGAM mechanism. Differences in ozone concentrations can be attributed to the VOC treatment by the three mechanisms. The diurnal variability of pollution and ozone precursors is not captured (hourly correlation coefficients for O 3 ≤ 0.29). This might be attributed to the underestimation of NO x concentrations by local emissions by up to 50 %. For the fine particulate matter (PM 2.5 ), the lowest mean bias (9 µg m −3 ) is obtained with the RADM2-MADE/SORGAM mechanism, with overestimates in sulfate and ammonium aerosols. Overestimation of sulfate aerosols by this mechanism may be linked to the SO 2 oxidation in clouds. The MOSAIC aerosol mechanism overestimates PM 2.5 concentrations by up to 22 µg m −3 due to a more pronounced dust component compared to the other two mechanisms, mostly influenced by the dust inflow from the global model. We conclude that all three mechanisms are very sensitive to boundary conditions from the global model for both gas-phase and aerosol pollutants, in particular dust and ozone.

On the widespread enhancement in fine particulate matter across the Indo-Gangetic Plain towards winter

“…Regional Acid Deposition Model -2 nd generation (RADM2) 56 coupled with the Modal Aerosol Dynamics Model for Europe/Secondary Organic Aerosol Model (MADE/SORGAM) aerosol module 57,58 has been used to simulate the gas-phase chemistry and aerosols in the model. Application of this chemical mechanism showed small bias (~7%) in PM 2.5 simulation over Europe 59,60 . The schemes opted to parameterize different processes in the model (Table S1) are based on earlier studies over this region using the WRF-Chem model 32,34,35 .…”

Evaluation of EU air quality standards through modeling and the FAIRMODE benchmarking methodology

“…Specifically for the country of Cyprus, studies indicate that the global top-down anthropogenic inventories do not adequately represent the gradient of emission fluxes between rural and populated areas, leading to an underestimation in modeled nitrogen oxide levels and overestimation of ozone levels in urban zones (Kushta et al 2017 ; Georgiou et al 2018 ). It is anticipated that the use of an up-to-date high-resolution (< 2 km) and temporally resolved (diurnal to seasonal) national emission inventory encompassing ground-based and satellite information and an accompanying model configuration with similar grid spacing can help capture the magnitude of emission fluxes and ozone levels in urban areas.…”

Exploring sources of uncertainty in premature mortality estimates from fine particulate matter: the case of China

“…Despite many attempts to validate and improve CTM results (Vautard et al 2007), inaccuracies in CTM output systematically occur due to improper spatial resolution (Crippa et al 2017), lack of accurate input data (e.g. emissions estimates (Zheng et al 2017a)), uncertain initial and boundary conditions (Georgiou et al 2018), and incomplete understanding of some physical-chemical processes (e.g. formation of secondary organic aerosol (Giani et al 2019)).…”